weight_error: Weighting and pooling methods on the basis of their error

In yvesmauron/univariate-time-series-forecasting: Intelligent Algorithms to be Integrated in Business Intelligence solutions.

Description

Weighting and pooling methods on the basis of their error

Usage

weight_error(weight_fun, error, y_hat, pool_limit, ...)

Arguments

weight_fun	weight function
error	the error vector which should be weightened
pool_limit	the pool size to be considered (e.g. 3 would indicate that only the best three methods would be selected)
...	passed to weight_fun

Value

the weights

yvesmauron/univariate-time-series-forecasting documentation built on March 2, 2020, 12:20 a.m.